Demographics

Model Results

About

The data set contains simulated hospital admission records of 10,000 heart failure (HF) patients. Each patient has a single record corresponding to the patient’s first HF admission (i.e. the index admission).

Abbreviation	Description
Patient_ID	Patient ID (1 through 10,000)
bdat	Date of birth
admdat	Index admission (I.e. first HF admission) date
sex	Sex
insur	Primary insurance type
readmreason	Reason for readmission: HF, AMI, Stroke, TIA or Other
readmdat	The date of first readmission after the index admission
deathdat	Date of death

Study endpoints include all-cause death, all-cause readmission and HF readmission. The outcomes are not explicitly defined: NAs in deathdat and readmdat columns signify that the event did not occur until the end of the study (31/12/2015). Each event can be defined within a given time interval (e.g. 30, 60, 90, 180 days, 1 year from the index admission, etc.) and analyzed using, for example, logistic regression. Since both, the date of the index admission and the date of an event are known, survival analysis can also be done. Think of using birth dates as well, e.g. age at the index admission as a covariate in the model, age cohorts, etc.). For the all-cause readmission, the distribution of reasons for the readmission can also be studied.

Comorbidities defined at the time of index admission. These include chronic conditions (hypertension, COPD, diabetes, etc.) as well as prior cardiovascular events (AMI, stroke, TIA, etc.). You can define your own inclusion/exclusion criteria, e.g. cancer.

Abbreviation	Description
ami	Acute Myocardial Infarction
stroke	Stroke
tia	Transient Ischemic Attack
hyp	Hypertension
asc	Atherosclerosis
cmyo	Cardiomyopathy
anem	Anemia
lipid	Disorders of Lipid Metabolism
diab	Diabetes
obes	Obesity
cld	Chronic Liver Disease and Cirrhosis
kd	Chronic Kidney Disease/Acute Kidney Failure
copd	Chronic Obstructive Pulmonary Disease
sleep	Sleep Apnea
thyr	Thyroiditis
cancer	Cancer